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Inferring a district-based hierarchical structure of social contacts from census data.

Yu Z, Liu J, Zhu X - PLoS ONE (2015)

Bottom Line: We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions.Second, the newly generated social contact patterns reflect individuals social contacts.Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China.

ABSTRACT
Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual's social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model.

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Related in: MedlinePlus

Comparison of the age- and district-specific disease attack rates in Hong Kong.
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pone.0118085.g013: Comparison of the age- and district-specific disease attack rates in Hong Kong.

Mentions: We also compare the age- and district-specific disease attack rates to explore whether the generated hierarchical contact structure can reproduce the observed dynamics of a spreading disease. The age- and district-specific disease attack rates are defined as follows:Λh=Ih∑kIk(22)Λi=Ii∑jIj(23)where h, k ∈ {1, …, a}, a is the number of age groups, i, j ∈ 1, …, r and r is the number of districts. Fig. 13 compares the simulated and real results of the age- and district-specific disease attack rates in Hong Kong. The simulation results are close to the real results, as shown in Figs. 13 (a) and (b), especially the results in the A1 age group in Fig. 13 (a) and the results of the R1 district in Fig. 13 (b). The hierarchical contact structure can improve our understanding of epidemic dynamics.


Inferring a district-based hierarchical structure of social contacts from census data.

Yu Z, Liu J, Zhu X - PLoS ONE (2015)

Comparison of the age- and district-specific disease attack rates in Hong Kong.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4356714&req=5

pone.0118085.g013: Comparison of the age- and district-specific disease attack rates in Hong Kong.
Mentions: We also compare the age- and district-specific disease attack rates to explore whether the generated hierarchical contact structure can reproduce the observed dynamics of a spreading disease. The age- and district-specific disease attack rates are defined as follows:Λh=Ih∑kIk(22)Λi=Ii∑jIj(23)where h, k ∈ {1, …, a}, a is the number of age groups, i, j ∈ 1, …, r and r is the number of districts. Fig. 13 compares the simulated and real results of the age- and district-specific disease attack rates in Hong Kong. The simulation results are close to the real results, as shown in Figs. 13 (a) and (b), especially the results in the A1 age group in Fig. 13 (a) and the results of the R1 district in Fig. 13 (b). The hierarchical contact structure can improve our understanding of epidemic dynamics.

Bottom Line: We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions.Second, the newly generated social contact patterns reflect individuals social contacts.Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model.

View Article: PubMed Central - PubMed

Affiliation: School of Computer Science and Engineering, South China University of Technology, Guangzhou, Guangdong, China.

ABSTRACT
Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual's social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model.

Show MeSH
Related in: MedlinePlus